Readmission Prevention

Avoidable readmissions is a costly dilemma for healthcare organizations that are at risk for millions of dollars in regulatory penalties. With Actian’s powerful analytics models, at-risk patients can be identified at the time of admission, enabling hospital staff to make immediate and more informed patient-centric care decisions.

Readmission_Prevention

Avoid Costly Readmissions with Predictive Analytics

  • Identify readmission risk at time of admission
  • Trigger the right hospital workflows so that interventions can be tailored at the individual patient level
  • Gain real-time insight into patient risk score as events occur during hospital stay
  • Extend your readmissions models for appropriate post-discharge follow-up

 

  • Optimize cost and utilization to reduce readmission rates and avoid CMS penalties
  • Personalize patient engagement by providing the correct level of interaction and treatment, resulting in increased patient satisfaction.
  • Integrate multiple data sources to analyze complete patient records

 

Staff Optimization

Staff resources are a critical element in a hospital’s cost structure. Using Actian’s powerful predictive analytics, hospitals can forecast patient volumes and leverage this information to help manage costs without diminishing patient outcomes.

 

 

Staff_Optimization

The right staff. The right patient. The right time.

  • Accurately predict patient inflow at any given time to generate staffing plans, resulting in reduced staff costs, minimal wait times, and improved employee satisfaction
  • Integrate historical data with limitless data sources to gain more accurate staffing models
  • Improve overall patient satisfaction by having the right staff available at the right time

 

  • Reduce the time spent for the scheduling process by using a dynamic tool that considers a variety of factors (e.g., work agreements, PTO requests, certification time, shift swaps, etc.) required for generating a patient-optimized schedule
  • With predictive analytic insights and alerts, administrators can manage to patient and financial targets (e.g., patient volume, wait times, PTO utilization, over-time, etc.)

 

Clinical Auto-Coding (CAC)

Improve efficiency, accuracy, and revenue capture of medical coding activities within healthcare organizations using CAC analytics. Actian’s predictive model reads structured and unstructured data, allowing the coding process to be automated and error-free at the time of entry.

 

 

Updated Test for CAC

Deliver Higher Medical Coding Accuracy

  • Increase financial and processing accuracy while reducing A/R outstanding days, denials and need for claims reprocessing
  • Automate the coding workflow with machine learning algorithms
  • Leverage a comprehensive medical vocabulary, including ICD-9 and ICD-10
  • Gain immediate insight on clinical codes from both structured and unstructured text

 

  • Detect errors in coding
  • Integrate with existing HIT and EMR systems via HL7
  • Prevent revenue leakage with clinical code recommendations

 

ACO Reporting

Actian’s ACO Reporting solution provides comprehensive, normalized real-time reporting of ACO measures across all your facilities, allowing your providers to focus on improving quality of care, containing cost, and driving efficiency for total population health management.

 

 

Final ACO Reporting

Improve Patient Outcomes with Accurate Reporting

  • Fulfill and exceed CMS reporting requirements, including shared savings/losses information and claims-based and administrative quality measures
  • Integrate both structured (e.g., claims data) and unstructured data sources (e.g., EMR)  to obtain complete and immediate visibility into the performance of your network, including trends, cost and utilization reporting, patient risk profiles, population health segmentation, chronic health management, etc.

 

  • Update reporting data in batch or real-time for increased precision
  • Leverage critical data from your network to empower providers with insights and workflows to improve patient engagement and promote population health management